Progress in Neuro-Psychopharmacology and Biological Psychiatry
Unraveling the biological mechanisms in Alzheimer's disease — Lessons from genomics
Research Highlights
► Exciting new GWAS data have emerged in the last few years, but it has become clear that common variants within the genome cannot fully explain the underlying genetic risk for AD. ► Novel approaches such as genome-wide analysis of copy number variations (CNV) or low-frequency rare functional gene variants may provide additional insight into genetic basis of AD. ► The review summarizes the findings of eighteen GWAS studies in AD performed to date, with an emphasis on potential future developments in the quest for genetic risk factors of AD.
Introduction
Alzheimer's disease (AD) is the most common form of dementia and the most common neurodegenerative disease. The estimated prevalence of the disease in 2006 was approximately 27 million people, with the highest number of patients present in the regions of Asia and Europe (Brookmeyer et al., 2007). The number of patients with dementia is increasing by roughly 4.5 million people annually (Ferri et al., 2005), and is projected to reach more than 115 million by the year 2050 (Prince and Jackson, 2009).
The disease is characterized histopathologically by the accumulation of β-amyloid plaques and neurofibrillary tangles, leading to progressive neuronal and synaptic loss in the limbic and association areas of cortex and in subcortical nuclei (Selkoe, 1991, Chertkow et al., 2001, Tiraboschi et al., 2004, Takashima, 2009). The AD patients exhibit a plethora of symptoms related chiefly to progressive cognitive and functional decline (Waldemar et al., 2007). The pathogenesis of AD still remains not fully elucidated, but deposition of β-amyloid (Aβ) 1–42 derived from amyloid precursor protein (APP), appears to be a key element contributing to oxidative stress, tau pathology, mitochondrial insufficiency and synaptic failure. Aβ, which is the major component of senile plaques, is cleaved from APP first by β-secretase, and then by the γ-secretase.
Genetic background of the disease is heterogeneous and complex, without a straightforward mode of inheritance. The patients can be divided in two major forms of the disease, namely those with an early age of onset, usually below 65 years of age, and patients with the late onset AD (LOAD), typically well beyond 65 years. The patients with early onset of the disease show Mendelian transmission and are affected by mutations in three genes, which are all involved in the production of Aβ (Tanzi and Bertram, 2005). The mutations affect the APP (Goate et al., 1991), presenilin 1 (PSEN1; Sherrington et al., 1995) and presenlin 2 (PSEN 2; Levy-Lahad et al., 1995, Rogaev et al., 1995) genes, interfering with the normal cleavage of APP by the γ-secretase complex.
Overwhelming majority of AD patients exhibit the late onset of the disease and show less-obvious familial aggregation. Despite strong evidence of heritability (Bergem et al., 1997, Gatz et al., 2006), genetic mechanisms involved in late onset AD have been much more difficult to elucidate. The disease pathophysiology in these patients is most likely linked to a whole set of susceptibility genes affecting various pathways, including those involved in Aβ production, such as SORL1, GAB2 or CH25H (Andersen et al., 2005, Zerbinatti et al., 2008), aggregation, such as CST3 or PRNP (Kaeser et al., 2007, Schwarze-Eicker et al., 2005), and clearance, such as ACE (Bertram and Tanzi, 2009, Sleegers et al., 2010). The role of several other susceptibility genes has also been implicated in other pathophysiological pathways, such as TF, MAPT and GAB2 in oxidative stress (Yamamoto et al., 2002, Ballatore et al., 2007, Nizzari et al., 2007), CHRNB2 in Ach transmission (Oddo and LaFerla, 2006), CR1 and CLU in inflammation damage (Khera and Das, 2009, Zanjani et al., 2005) or PICALM in intracellular trafficking of synaptic vesicle proteins (Harel et al., 2008). Over past several decades, more than 500 genes have been associated with increased risk of AD, mainly by utilizing the candidate gene approach (Bertram and Tanzi, 2008).
Despite the large number of candidate genes, only a few have been reproducibly shown to influence disease risk or onset age (Bertram et al., 2007). Among those genes, the ε4-allele of the apolipoprotein E gene (APOE) has shown the strongest risk effect for the development of AD (Strittmatter et al., 1993, Saunders et al., 1993). APOE is found within senile plaques (Namba et al., 1991), binds Aβ (Strittmatter et al., 1993), may influence neuritic formation of plaques in mouse models of the disease (Holtzman et al., 2000) and is involved in Aβ deposition and clearance in the brain (Holtzman, 2004). Despite the strong evidence for its role in disease pathophysiology, APOE as a genetic risk factor is not fully penetrant, and is neither necessary nor sufficient for the development of AD (Ertekin-Taner, 2010). Heterozygous carriers of the ε4 genotype exhibit a two to four times greater AD odds ratio when compared to homozygous ε3 carriers. In homozygous ε4 carriers the odds ratio increases to 6 to 30, as shown in population-based studies in subjects of European origins (Ertekin-Taner, 2007). However, the effect of APOE ε4 seems to be age dependent, and its use as a diagnostic and predictive factor in a clinical setting is not feasible (Knopman et al., 2001).
Deciphering of the human genome and development of high-throughput genomic technologies (Manolio and Collins, 2009) have accelerated the efforts aimed at unraveling of underlying pathophysiological mechanisms involved in AD. These achievements opened up novel major avenues of scientific effort in research of AD. A new impetus was given to the search for candidate genes associated with increased risk of AD especially through performing genome-wide association studies (GWAS). In this review we give a comprehensive overview of the GWAS studies in AD performed so far, providing a novel overview of several GWAS approaches, from case–control studies, to copy number variations (CNV) analysis to quantitative-trait association studies. Furthermore, we also give emphasis on novel avenues of research, such as genome-wide analysis of CNV or low-frequency rare functional gene variants.
Section snippets
Genome-wide association studies in AD
Detailed identification and characterization of single-nucleotide polymorphisms (SNPs) in the human genome (Sachidanandam et al., 2001) and development of novel high-throughput SNP genotyping technologies enabled a more comprehensive insight into the genetic basis of common, complex diseases. In contrast to candidate gene studies, which do not allow results beyond the scope of the initial hypothesis, GWAS allow for simultaneous testing of a very large number of genetic markers. The studies
The study of Heinzen et al. (2010)
A growing number of studies have suggested that structural variation, including CNVs, may contribute to human disease (Estivill and Armengol, 2007) and a rare duplication of APP has already been linked to early onset AD. Using 331 AD cases and 368 controls of European ancestry, the authors conducted genome-wide genotyping on Illumina Human HapMap550K microarrays (Heinzen et al., 2010). GWAS results showed that only one SNP in the TOMM40 gene, located upstream of APOE ε4 gene, achieved
The study of Potkin et al. (2009)
Trying to apply quantitative-trait association approach, Potkin and coworkers combined the neuroimaging data of hippocampal gray matter density MR measurements with results of the Illumina Human610 Quad microarray genotyping (Potkin et al., 2009). The study consisted of 172 AD cases and 209 controls of European ancestry from the Alzheimer's Disease Neuroimaging Initiative study. In the first part of the study, the authors performed a standard case–control study, which confirmed the association
Discussion
Despite considerable advances in our understanding of genetic mechanisms involved in development of AD brought about by application of powerful high-throughput genome-wide association studies, full elucidation of the genetic disease risk factors is still evading scientists working in the field. In this review we have described results of eighteen studies utilizing different approaches to assess genome-wide association significance, varying from traditional case–control GWAS studies, to CNV
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